Fig 3. CT-based fibrosis prediction. (IMAGE)

Research

Fig 3. CT-based fibrosis prediction.

Caption

Fig 3. CT-based fibrosis prediction. (A) Workflow of radiomics analysis. (B) SHAP summary plot showing the top 15 radiomic features contributing to fibrosis prediction. (C) Fivefold cross-validation performance of the CT-based fibrosis prediction model on the training (SYSUCC) and test (XHCSU) cohorts. (D) Representative contrast-enhanced CT  images with discriminative textural feature maps in high- and low-fibrosis patients. (E) Performance comparison of different fibrosis prediction models using features extracted from venous-phase CT images. (F) Performance comparison of different CT imaging phases. SVM classifiers were built using features extracted from arterial-, venous-, and delayed-phase images, as well as their average combination. AUC, area under the receiver operating characteristic curve; ACC, accuracy; A, arterial phase image; V, venous phase image; D, delayed phase image.

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Copyright © 2025 Qiuxia Yang et al.

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